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Modelling the impacts of land system dynamics on human well-being: Using an agent-based approach to cope with data limitations in Koper, Slovenia

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... Another ABM model sought to simulate the effects of urban growth on land use, particularly for agriculture, in Koper, Slovenia (Robinson et al., 2012). ABM was chosen in part because of lack of availability of land-use data that prohibited an alternative modeling type. ...
... ABM was chosen in part because of lack of availability of land-use data that prohibited an alternative modeling type. The researchers used the concept of an 'agent' to represent actors that make land-use decisions, but for which they had little empirical data (Robinson et al., 2012). Drawing from what landuse data the researchers could find, they were able to combine this with agent decision-making trees, applying inductive and deductive approaches to calculate probabilities for agent actions to then simulate potential outcomes (Robinson et al., 2012). ...
... The researchers used the concept of an 'agent' to represent actors that make land-use decisions, but for which they had little empirical data (Robinson et al., 2012). Drawing from what landuse data the researchers could find, they were able to combine this with agent decision-making trees, applying inductive and deductive approaches to calculate probabilities for agent actions to then simulate potential outcomes (Robinson et al., 2012). ...
Article
In a world of increasing population and decreasing availability of arable land, the need to maintain and improve the quality of our farm systems is a clear and pressing one. Considerations of different types of capital give us a more holistic picture of what is at stake. Our decision-making mechanisms and tools must seek to integrate all types of capital, including natural and social capital, if we are to sustain long-term farm performance. Modeling is one way to integrate this ‘expanded’ notion of capital. While farm modeling is not a new concept, this paper reviews various types of models with the aims of determining which is most suitable to demonstrate the effect of natural and social capital on farm risk, farm resilience, and farm well-being. As an industry particularly vulnerable to extreme weather patterns and other ecological hazards, the concepts of risk and resilience are critical to sustain long-term farm well-being. Various types of farm models are covered in this review, including land use cover and change, agent-based, statistical, system dynamics, and participatory modeling. The paper also identifies key characteristics that assist in modeling the effects of natural and social capital management. I conclude that an integrated, spatially explicit, participatory, systems-based modeling process is suggested to usefully incorporate natural and social capital effects on farm risk, resilience, and well-being. This approach can incorporate a whole systems approach, capture system ‘leverage points’, and effectively involve affected stakeholders.
... Many of scholars have tried to exploit integrated agent-based modeling with cellular automata to simulate spatial pattern of urban growth and other fields of social science. In most of these studies, the cellular automata is utilized to define environmental infrastructure, whilst the agent-based modeling approach is used to model the complex behavior of residents which involves various agents in forming urban morphology (Li and Liu, 2007;Robinson et al., 2012). For instance, Robinson et al. integrated cellular automata rules into agent-based modeling approaches to simulate the behaviors of different organizations in urban growth modeling. ...
... Also, they evaluated the effects of the land use system on the people's life and their agricultural systems. The results of the models demonstrated that the urban growth had disproportionately impacts on the agricultural lands (Robinson, Murray-Rust, Rieser, Milicic, & Rounsevell, 2012). In some other studies, agentbased models are combined with other methods such as mathematical models and heuristic algorithms to improve the predictions. ...
Article
Population increase and industrialization, particularly in developing countries, has led to the rapid growth of urban areas. To adequately direct urban growth, provide access to urban facilities and preserve the environment, accurate planning is required. As part of urban planning, computer-based simulation models can be used to predict the natural growth of urban areas. The objective of this research is to develop an agent-based simulation model, with different temporal resolutions and reinforced by game theory, to predict the growth of Zanjan city between 2011 and 2016. In the model, three types of land developer, classified according to their income level, are considered as agents, with different attributes and behaviors. Agents search the cellular environment, collect data and select proper sites for development in accordance with their criteria and preferences. When several agents select a single cell for development, their competition is modeled by game theory. The agent-based model is implemented and tested in two scenarios: with game theory and without it. In addition, based on the fact that urban growth is a spatio-temporal phenomenon, different temporal resolutions of 6, 12, 30 and 60 months are considered in the implementation. Kappa statistics, Percent Correct Match, and figure of merit are used to compare the results of modeling scenarios with the urban map of 2016. The best result of 81.1%, 97.32% and 6.38% for Kappa statistics, Percent Correct Match and figure of merit are obtained, when game theory and 6-months resolution is used. The results showed that the usage of game theory and higher temporal resolution have both positive effects on the accuracy of the model. With higher temporal resolutions, the gradual developments of neighboring cells can well be considered by agents. Using game theory can help in modeling the competition-based interactions and behavior of agents.
... The advantage of ABM is that it has the capacity to go beyond some of the restrictive assumptions associated with other modelling techniques (such as cellular automata) in accommodating bounded rationality, heterogeneity among agents and out-of-equilibrium dynamics and interactions, enabling modellers to have flexibility in model design [14]. These advantages allow ABM-based approaches to incorporate human decision-making behaviours within the simulation of the urban development process [17][18][19]. As such, ABMs have received much attention in the urban modelling community in recent years with their application in a number of different contexts to simulate urban growth and land use change [17,18,20]. ...
... These advantages allow ABM-based approaches to incorporate human decision-making behaviours within the simulation of the urban development process [17][18][19]. As such, ABMs have received much attention in the urban modelling community in recent years with their application in a number of different contexts to simulate urban growth and land use change [17,18,20]. ...
Article
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In the provision of urban residential areas, private land developers play critical roles in nearly all stages of the land development process. Despite their important role little is known about how the spatial decisions of individual developers collectively influence urban growth. This paper employs an agent-based modelling approach to capture the spatial decisions of private land developers in shaping new urban forms. By drawing on microeconomic theory, the model simulates urban growth in the Jakarta Metropolitan Area, Indonesia, under different scenarios that reflect the decision behaviours of different types of developers. Results reveal that larger developers favour sites that are more proximate to the city centre whilst smaller developers prefer sites that are located further away from the city, that drive a more sprawled urban form. Our findings show that new urban areas are generated by different developers through different processes. The profit maximisation behaviour by developers with large capital reserves is more predictable than those with small capital funds. The imbalance in capital holdings by different types of developers interacts with one another to exert adverse impacts on the urban development process. Our study provides supporting evidence highlighting the need for urban policy to regulate urban expansion and achieve more sustainable urban development outcomes in a developing world context.
... As the study of complexity complements reductionism rather than displaces it [68], so too can statistical models form the basis for agent-based approaches and the creation of hybrid models that utilize the best aspects of both approaches can be developed. For example, in the absence of data about actors driving industrial and commercial development, logistic regression was used to create a model rich in the number of land-use types (11) [69,70]. Not only did the logistic regression perform well, but the authors are aware of no examples of published research or researchers engaged in modelling the site-selection behavior of industrial and commercial actors using an agent-based modelling approach. ...
... The presented research contributes to a lack of literature on land-use change modelling where the focus is on high-fidelity parcel-level models, which is the scale at which land-use change decisions are made [69]. Future research will seek to extend the modelling comparison to other statistical modelling approaches as well as to investigate the outcomes of different scenarios of future land-use and land-cover change. ...
Article
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Land-use change can have local-to-global environment impacts such as loss of biodiversity and climate change as well as social-economic impacts such as social inequality. Models that are built to anaPlyze land-use change can help us understand the causes and effects of change, which can provide support and evidence to land-use planning and land-use policies to eliminate or alleviate potential negative outcomes. A variety of modelling approaches have been developed and implemented to represent land-use change, in which statistical methods are often used in the classification of land use and land cover as well as to test hypotheses about the significance of potential drivers of land-use change. The utility of statistical models is found in the ease of their implementation and application as well as their ability to provide a general representation of land-use change, given a limited amount of time, resources, and data. Despite the use of many different statistical methods for modelling land-use change, comparison among more than two statistical methods is rare and an evaluation of the performance of a combination of different statistical methods with the same dataset is lacking. The presented research fills this gap in land-use change modelling literature using four statistical methods—Markov chain, logistic regression, generalized additive models and survival analysis—to quantify their ability to represent land-use change. The selection of these methods is based on criteria: (1) the popularity of a method, (2) the difficulty level of implementation, and (3) the ability of accounting for different scenarios. The four methods were compared across three dimensions: accuracy (overall and by land-use type), sample size, and spatial independence via conventional and spatial cross-validation. Our results show that generalized additive model outperformed the other three in terms of overall accuracy and were the best for modelling most of land-use changes with both conventional and spatial cross-validation regardless of sample size. Logistic regression and survival analysis were more accurate for specific land-use types, and Markov chain was able to represent those changes that could not be modeled by other approaches due to sample size restrictions. The overall spatial cross-validation accuracies were slightly lower than the conventional cross-validation accuracies. Our results also demonstrate that not only is the choice of model by land-use type more important than sample size, but also that a hybrid land-use model comprising the best statistical modelling approaches for each land-use change outperformed the individual statistical approaches. While Markov chain was not competitive, it was useful in providing representation using other methods or in other cases where there is no predictor data.
... Liu and Ma, 2011;Shu et al., 2014); (ii) projecting future scenarios and their potential impacts (e.g. Mustafa et al., 2016;Robinson et al., 2012); and (iii) evaluating the impacts of different spatial policies on land-use patterns (e.g. Guzy et al., 2008;Jantz et al., 2003). ...
... In a large study area, such an intensive data gathering is limited by the presence of a large number of agents (Valbuena et al., 2008). In order to overcome data limitations, a number of studies used empirical data, such as distance to road network, slope etc., to represent agents decision-making for which we have no behavioral information (Mustafa et al., 2017a;Robinson et al., 2012). ...
Thesis
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The main goal of this PhD research is to investigate the expected flood damage for future urban patterns at different scales. Four main steps are followed to accomplish this goal. In the first step, a retrospective analysis is performed for the evolution of the urban development in Wallonia (Belgium) as a case study. Afterward, two land use change models, cellular automata-based, and agent-based are proposed and compared. Based on this comparison, the agent-based model is employed to simulate future urbanization scenarios. An important feature of this research is evident in the consideration of the multiple densities of built-up areas, which enables to study both expansion and densification processes. As the model simulates urbanization up to 2100, forecasting land use change over such time frames entails very significant uncertainties. In this regard, uncertainty in land use change models has been considered. In the third step, 24 urbanization scenarios that differed in terms of spatial policies and urbanization rate are generated. The simulated scenarios have then been integrated with a hydrological model. The results suggest that urban development will continue within flood-prone zones in a number of scenarios. Therefore, in the fourth and last step, a procedural urban generation system is developed to analyze the respective influence of various urban layout characteristics on inundation flow, which assists in designing flood-resistant urban layouts within the flood-prone zones.
... The indirect influence of the interactions among these social parties are concerned but not well represented in the model. For instance, in some models even though industries are included (Jjumba and Dragic´evic´, 2012;Robinson et al., 2012;Zhang et al., 2013), the mechanism of their relationship with urban macro-economy, urban employment rate and the workers' (residents') income is overlooked. ...
... Different from other studies on industries' influence upon urban land use (Jjumba and Dragic´evic´, 2012;Robinson, et al., 2012;Zhang et al., 2013), this paper not only integrates factors of decision making (by the urban government) to the model and analysis, but also takes into account the mechanism of the relationship between firm-/ worker-level behaviours with the overall performance of the urban economy, and the mutual dependence of the firms and the workers. These underlying connections influence urban land-use change indirectly and thus have been overlooked by the literature listed above. ...
Article
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Much of the focus of research on creative industries’ influence upon urban land use has been around the investment in specific regeneration projects or flagship developments rather than addressing the nature and location of the infrastructure, networks and agents engaged. In other words, the complexity of the institutional/temporal and spatial interaction among the involved elements is overlooked or not well understood. This paper presents an agent-based model named CID-USST (Creative Industries Development-Urban Spatial Structure Transformation) that examines the dynamics of the interaction between the development of creative industries and urban spatial structure by outputting a set of adaptive scenarios through time and space. It reveals that the spatial distribution of both the creative firms and the creative workers evolves in a repeating up-and-down pattern even when the exogenous urban economic condition is set to be steady. Moreover, the analysis also points to the policy implication that more open job/rent market information will lead to more rapid geographical clustering of the creative firms and the creative workers, which possibly may reduce the time cost in their spatial evolvement, and perhaps accelerate innovation if we accept that geographical proximity can enhance knowledge and information spill-over.
... Thanks to the cohesion policy, cities have been able to obtain resources to deal with many problems associated with the growth of urban agglomerations. For example, as cities develop, environmental problems reducing the quality of life, such as air pollution and disappearance of green spaces, are becoming more common [Robinson et al. 2012; Thompson et al. 2012;Mitchell 2013;Cloutier 2014]. Taking into account the importance of EU funds in urban development, their impact on the quality of life should be examined. ...
Article
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Contemporary urban policies pay great attention to improving the quality of life of the inhabitants. Such an increasing interest in the quality of life is caused by its crucial importance for the location decisions of households and businesses. In recent years, urban development has been largely financed by EU cohesion policy funds. The paper intends to identify the areas in which the quality of life of the inhabitants of large cities in Mazovia has improved thanks to the implementation of cohesion policy. The study took into account large cities in Mazovia with over 100,000 inhabitants, i.e. Warsaw, Radom and Plock. The survey is based on data collected for the research project: ‚The impact of the cohesion policy on urban development in 2007–2013’, provided by the Ministry of Development. This includes in-depth interviews with representatives of units responsible for development strategy in the cities covered by the survey and a questionnaire survey among beneficiaries of projects co-funded by EU funds. An analysis of databases of projects implemented in large cities in Mazovia, financed with the participation of EU funds, as well as a research of literature on the quality of life in cities in Mazovia were also conducted. The results indicate that the inhabitants see the most improvement in the quality of life in connection with better transport in the cities. The quality of life has increased thanks to faster and more comfortable commuting to work, which leaves more time for other activities and spending free time.
... And the omission of some important development activities, like the allocation of public service and infrastructure facilities, could also cause severe deviation in its final simulation results, due to the fact that the mutual influences among different urban land use may sometimes play a more important than market profits in resident's decision-making process, just like people do in the NIMBY phenomenon. Therefore, in order to explore the internal operation mechanism for urban land system in San Diego and to make accurate predictions about its future development trend, this simulation research will choose three most important land use types (residential, industrial and commercial) (Robinson et al., 2012) as its research targets and design modeling behavior rules for each one of them separately, so that it could conduct research on future land development through different kinds of interactive activities among agents and their surrounding environment. ...
... • The demographic and associated land use development of a city, including green space and other urban ecosystems (Hayek et al., 2015;Ligmann-Zielinska and Jankowski, 2007), and their impacts on human well-being and quality of life (Murray-Rust et al., 2013;Robinson et al., 2012); • The diffusion of rainwater catchment and collection green infrastructure, systems, and knowledge amongst citizens (Kandiah et al., 2017;Montalto et al., 2013). ...
Article
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Embedding nature-based solutions (NBS) in cities is expected to bring quantifiable benefits, including resilience to flooding, drought, and heatwaves, and air quality improvement. Among NBS, green roofs have an important role in temperature regulation in buildings and in lowering the damaging effects of heatwaves on human health. In this paper a spatial microsimulation model is implemented to simulate temperature impacts of green roofs installations in cities and their capacity to attenuate the effects of heatwave episodes. Particularly vulnerable to heatwaves are elderly people with limited mobility, who have limited means to seek cooling and create cooler indoor environments. The model, implemented using the Netlogo platform (version 6.0.4), considers as agents the elderly citizens in a city area and simulates the heatwave-related health impacts, which are measured in mortality likelihood. In particular, the model simulates a generalised 1.5 °C to 3 °C indoor temperature reduction range induced by green roofs (based on inferences from green roof literature) in four different European cities: Szeged (Hungary), Alcalá de Henares (Spain), Metropolitan City of Milan (Italy) and Çankaya municipality (Turkey). The simulation utilises a ceteris paribus modelling approach, meaning that the relationships of the observed phenomenon (mortality induced by heatwaves) with other possible influencing factors (e.g. level of sport and physical activities practiced by people) are not taken into account. In the case of Szeged, Alcalá de Henares, and Çankaya municipality a substantial reduction in mortality is found to occur associated with green roofs roll out. In the case of the Metropolitan city of Milan, green roofs installations show a low mitigation effect in some scenarios. The underlying factor is the temperature threshold parameter of the model, above which heatwave mortality occurs. This parameter was inferred from the literature (Baccini M., et al., 2008) and it resulted to be substantially higher in the Metropolitan city of Milan (31.8 °C) than in the other cities. The simulation helps in obtaining results which are specific to a given city and particular scenarios therein, and provides additional insights, such as expected temperature mitigation effect induced by green roofs under climate change conditions, or the indoor temperature reduction targets that are needed for a particular city to have a maximum desired heatwave mitigation impact. However, the model parameters have to be carefully selected, after an accurate study of the domain literature.
... The availabilities of social amenities, food production capacities, communications and economic factors determine settlement locations (Fragkias & Seto, 2009;Lin et al., 2012). Factors such as water availability, nearness to transport facilities and topography often influence settlement locations (Robinson et al., 2012;Su et al., 2011); thereby leading to uneven distribution of human settlements across different spatial measures. In-depth cognizance of ecological procedures, land use/land cover changes, lifestyles and cultures are derived when spatial patterns of settlements are analysed. ...
Article
Spatial patterns of human settlements, their changes and their geographical implications are important for understanding the drivers of land use and land cover change. This paper examines the spatiotemporal pattern of settlement development in three different settlements of Thabo Mofutsanyane municipal district namely Harrismith, Vrede and Ladybrand using GIS, remote sensing and spatial metrics techniques. The study is based on 30 years of time-series data compiled from satellite images with emphasis on pre and post 1994’s (the year of change in government from apartheid to majority rule) spatial change in settlement development. Landsat 4–5 imageries for 1989, 1999, 2009 and Landsat 8 OLI for 2018 were downloaded and classified for land use/land cover change (LULCC). Also, landscape and class metrics were computed using Fragstats QGIS 2.18.9 to generate spatial analysis. A dynamic spatial pattern is observed in the settlements under study. Urban built-up areas had a rapid trend of growth in Harrismith from 1989 (5 years before transition from apartheid to majority rule) to 1999 (5 years after transition from apartheid to majority rule) but later slowed down in the subsequent years under study while Ladybrand and Vrede had moderate growth trend in the subsequent years under study. The settlement development process has developed fragmented and heterogeneous land use combinations in the years after 1994. At landscape level, land fragmentation occurred due to land use changes and significant urban expansion; Ladybrand experienced more physical connectedness than Harrismith and Vrede. While at class level, Harrismith and Vrede are more aggregated or physically connected than Ladybrand; this means Ladybrand was relatively more fragmented than the other two settlements. The study results show that a LULCC and landscape metrics integrated approach is effective to analyse and describe the spatial patterns of urban landscapes.
... On the other hand, the modelers of ABM tend to take a bottom-up, disaggregate approach that looks at the "behaviors through which individuals interact with one another" (Parunak, Savit, and Riolo 1998, 19). Nevertheless, the two fields are not hermetic, and there can be a hybridization of methods, in other words, ABM using the equation-based method as a first instance for identifying patterns and processes (e.g., Robinson et al. 2012;Robinson and Brown 2009). We should see the integration of ABM and cellular automata (CA) as a result of a revolution during the past thirty years. ...
Article
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The term “behavioral” has become a hot topic in recent years in various disciplines; however, there is yet limited understanding of what theories can be considered behavioral theories and what fields of research they can be applied to. Through a cross-disciplinary literature review, this article identifies sixty-two behavioral theories from 963 search results, mapping them in a diagram of four groups (factors, strategies, learning and conditioning, and modeling), and points to five discussion points: understanding of terms, classification, guidance on the use of appropriate theories, inclusion in data-driven research and agent-based modeling, and dialogue between theory-driven and data-driven approaches.
... Researches show that the urban growth is a dynamic system and therefore it is highly complex and non-linear in nature. From all existing approaches, the cellular automata modelings (Clarke et al., 1996;Clarke et al., 2001), agent-based modelings (Robinson et al., 2012;Arsanjani et al., 2013), spatialstatistics modelings, artificial neural network modelings (Pijanowski et al., 2009;Mohammady et al., 2014) and fractal modelings (Herold et el., 2002;Triantakonstantis, 2012) are the most used in the last two decades. Among all dynamic models spatially explicit, those based on CA are more common for their applications in urban areas. ...
Article
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Many studies, using various modeling approaches and simulation tools have been made in the field of urban growth. A multitude of models, with common or specific features, has been developed to reconstruct the spatial occupation and changes in land use. However, today most of urban growth techniques just use the historical geographic data such as urban, road and excluded maps to simulate the prospective urban maps. In this paper, adding buildings and population data as urban fabric factors, we define different urban growth simulation scenarios. Each simulation corresponds to policies that are more or less restrictive of space considering what these territories can accommodate as a type of building and as a global population. Among the urban growth modeling techniques, dynamic models, those based on Cellular Automata (CA) are the most common for their applications in urban areas. CA can be integrated with Geographical Information Systems (GIS) to have a high spatial resolution model with computational efficiency. The SLEUTH model is one of the cellular automata models, which match the dynamic simulation of urban expansion and could be adapted to morphological model of the urban configuration and fabric. Using the SLEUTH model, this paper provides different simulations that correspond to different land priorities and constraints. We used common data (such as topographic, buildings and demography data) to improve the realism of each simulation and their adequacy with the real world. The findings allow having different images of the city of tomorrow to choose and reflect on urban policies.
... On the methodological side, this investigation could be explored by taking advantage of the developments in computer software and hardware, as well as in the availability of new local and regional social surveys, as suggested by Ballas (2013). Useful empirical methods are spatial microsimulation (Ballas and Clarke, 2000;Ballas, 2004;Ballas and Clarke, 2001;Ballas et al., 2005Ballas, 2010, GIS-based (Marans & Stimson, 2011, inter alia) or agent-based models (Robinson et al., 2012). Furthermore, extending the period of observation would make it possible to evaluate whether the 2008 recession played a role in explaining the dynamics of happiness. ...
Article
The paper investigates how traits of cities explain subjective well-being and its subcomponents. Building up a happiness function, where life satisfaction is determined by satisfaction on life domains, the impact of city-level determinants of happiness is analyzed through a multilevel analysis. The results show that Italian cities have an effect on subjective well-being through different happiness domains. The relationship between the estimated coefficients of domain satisfactions and some relevant urban-context variables and amenities is then examined. This approach allows urban policy agendas to be designed around city-specific characteristics.
... In this context, the habitat space reflects a social structure (Zhang, 2000). Moreover, human geographers who have investigated the interactions between human settlements and the natural environment have focused on the spatial forms of settlements in terms of the human-earth relationship (Gude et al., 2006;Robinson et al., 2012;Xi, 2011). Moreover, architectural researchers have focused on spaces rather than social aspects (Fuji, 2000). ...
Article
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This study investigates the characteristics of spatial elements and structure in a multi-cultural traditional settlement in Degger County, Sichuan Province, in the Tibetan area of China. This study aims to clarify the geometric spatial representation of traditional settlements. The geometric features of their settlement plans are compared using mathematical analysis after examining the spatial arrangement of four typical settlements. Results indicate that the settlement structure has strong centrality. The spatial structure characteristics and proposed spatial models of traditional settlements in this area are discussed to aim for the results to contribute to new village planning and preserve a traditional settlement heritage.
... iv) Agentbased modelling (e.g. Manson, 2005;Robinson et al., 2012), which simulate the actions and interactions of autonomous agents involved in LULC change. ...
... We report our results and discuss these in Section 4, with Section 5 presenting our conclusions. Aguayo et al. (2007) identified three main elements for land-use change spatial models: (i) examining the factors that control the change (e.g., Liu and Ma, 2011;Shu et al., 2014); (ii) projecting future scenarios and their potential impacts (e.g., Mustafa et al., 2016;Robinson et al., 2012);and (iii) evaluating the impacts of different spatial policies on land-use patterns (e.g., Guzy et al., 2008;Jantz et al., 2003). In line with the aims of this study, we focus on exploring the factors that control built-up development considering both expansion and densification processes. ...
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An in-depth understanding of the main factors behind built-up development is a key prerequisite for designing policies dedicated to a more efficient land use. Infill development policies are essential to curb sprawl and allow a progressive recycling of low-density areas inherited from the past. This paper examines the controlling factors of built-up expansion and densification processes in Wallonia (Belgium). Unlike the usual urban/built-up expansion studies, our approach considers various levels of built-up densities to distinguish between different types of developments, ranging from low-density extensions (or sprawl) to high-density infill development. Belgian cadastral data for 1990, 2000 and 2010 were used to generate four classes of built-up areas, namely, non-, low-, medium- and high-density areas. A number of socioeconomic, geographic and political factors related to built-up development were operationalised following the literature. We then used a multinomial logistic regression model to analyse the effects of these factors on the transitions between different densities in the two decades between 1990 and 2010. The findings indicate that all the controlling factors show distinctive variations based on density. More specifically, the centrality of zoning policies in explaining expansion processes is highlighted. This is especially the case for high-density expansions. In contrast, physical and neighbourhood factors play a larger role in infill development, especially for dense infill development.
... The location selection is influenced by geographical characteristics like topography, water accessibility or strategical purposes (e.g. Robinson et al. 2012, Su et al. 2011, Carrión-Flores and Irwin 2004, Warren 1990, Butzer 1982, Hodder and Orton 1976. In order to identify settlement patterns, two different approaches are commonly used, the social perspective and the ecological perspective. ...
Thesis
It is difficult to draw reliable conclusions about prehistoric cultures due to inherently vague archaeological data. The lack of suitable methods for the quantitative analysis of settlement patterns in terms of uncertain as well as incomplete data is the motivation for this research. The aim is to gain the maximum of information about former settlements with a minimum of previous knowledge. To achieve that goal, the environmental surroundings in combination with the location are considered in the analysis. This is based on mainly two assumptions, namely that locations of settlements are influenced by environmental conditions and that settlements have different functions within the settlement-network. Literature research was necessary in order to collect as many excavation site locations as possible. The result is the largest published collection of former settlement in the Amazon region. A conceptual data model is developed which fits the requirements of the available data and is implemented in a central database on a server in order to provide the data. This reduces redundancies and provides external access over the internet for all interested researchers. Consequently it facilitates the analysis of intra cultural settlement patterns. Additionally environmental variables need to be defined which are assumed to be potentially influencing. A knowledge discovery process is developed which allows to further analyse the data. A Maximum Entropy Model is performed to see whether an environmental variable is influencing the outcome of the model. The variables with an ascertainable contribution are used for further analysis. The settlement type is determined using a clustering approach on the basis of the remaining environmental variables. To avoid that distant variables distort the cluster result, only environmental variables near the excavation site are considered. The definition of nearness is made using a rough boundary which is individually set for each parameter. The maximum nearness value is randomly selected and used as input for the cluster analysis. Various cluster runs with changing maximum nearness values are performed and compared using the consensus clustering approach. An optimal cluster solution as well as a consensus value are returned as a result which is used in order to calculate settlement function related suitability surfaces. These cost surfaces serve as basis for the concluding territory analysis. The developed methodology allows to derive scenarios of potential functional settlement patterns. The focus is on archaeological records of yet poorly explored cultures.
... However, there are a limited number of studies that consider the expansion of several urban densities and/or densification in a variety of ways. Mustafa, Cools, Saadi, and Teller (2015), Robinson, Murray-Rust, Rieser, Milicic, and Rounsevell (2012), Sunde, He, Zhou, Hubbart, and Spicci (2014), Xian and Crane (2005), Yang (2010) and Zhang et al. (2011) model the expansion of different urban/built-up densities. Crols et al. (2015), Loibl and Toetzer (2003), White, Engelen, and Uljee (2015) and White, Uljee, and Engelen (2012) model the processes of urban expansion as well as of densification. ...
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This paper presents a model to simulate built-up expansion and densification based on a combination of a non-ordered multinomial logistic regression (MLR) and cellular automata (CA). The probability for built-up development is assessed based on (i) a set of built-up development causative factors and (ii) the land-use of neighboring cells. The model considers four built-up classes: non built-up, low-density, medium-density and high-density built-up. Unlike the most commonly used built-up/urban models which simulate built-up expansion, our approach considers expansion and the potential for densification within already built-up areas when their present density allows it. The model is built, calibrated, and validated for Wallonia region (Belgium) using cadastral data. Three 100 × 100 m raster-based built-up maps for 1990, 2000, and 2010 are developed to define one calibration interval (1990–2000) and one validation interval (2000 − 2010). The causative factors are calibrated using MLR whereas the CA neighboring effects are calibrated based on a multi-objective genetic algorithm. The calibrated model is applied to simulate the built-up pattern in 2010. The simulated map in 2010 is used to evaluate the model's performance against the actual 2010 map by means of fuzzy set theory. According to the findings, land-use policy, slope, and distance to roads are the most important determinants of the expansion process. The densification process is mainly driven by zoning, slope, distance to different roads and richness index. The results also show that the densification generally occurs where there are dense neighbors whereas areas with lower densities retain their densities over time.
... ribution License, which permits unrestricted Therefore, human settlement acts as the most fundamental link , and reflects the interaction of people with the surrounding environment (Fragkias and Seto, 2012). They are thus influenced to a large extent by topography, water accessibility, and transportation and Irwin, 2014; (Robinson, Rust, Milicic, and Rounsevell, 2012). Location of determined by local amenities, economic (Mueser and Graves, 1995; Sevenant Three spatial features impact the economic development of a region: the density (e.g. ...
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ARTICLE INFO ABSTRACT Human settlements provide a on the policy-spatial distribution of populations, settlements and their inter settlements is determined by local amenities, economic factors, and communications. Political transformations and instability conditions are among the most important factors economic, and environmental aspects witnessed wars and political problems. many political transformations and events since the occupation by the Israeli Army of the Palestinian Land in land use changes, ecological processes, and cultures. human to explore the distribution of Palestinian settlements and their communication in Jerusalem district under the political crisis such the popular uprising. including descr environment process, of human settlements and the geopolitical factors. settlements, segregation wall, and military checkpoints impacted negatively on Palestinian settlements and their inter These factors led to convert the Palestinian communities into islands in the Israeli colony ocean in Jerusalem district and isolate the Palestinian communities from each to other especial political crisis. of knowledge, Palestinian need to transition from reaction in the game by preparing an alternative plan and scenarios to meet the Israeli process in general and especially under political crisis and future popular uprisings urban and regional planners, and researchers need to pay more planning and research efforts to help the Palestinian communities Copyright © 2016, Samer Hatem Raddad. This is an open access use, distribution, and reproduction in any medium, provided the original work is properly cited.
... Land use and land cover change often exhibit specific dynamics, and these might very well impact the well-being of inhabitants. Agent-based simulations for the municipality of Koper, Slovenia, e.g. have shown that aggregate resident quality of life increases non-linearly when development density is changed; it also has been shown that clustering industrial development has benefits for human wellbeing [29]. Agent-based simulations also have been conducted for rural areas, e.g. ...
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Resilience-related topics have been gaining importance for urban planners and policy makers over the last decades. In this chapter, we argue that agent-based modeling (ABM) offers a promising tool to assess and test resilience-related measures which are planned and implemented in urban neighborhoods. We demonstrate potentials, but also limitations of the method, using the concept of ur-ban electricity sharing as a demonstration case. Electricity sharing systems are based on decentralized electricity generation and large batteries. The availability of such a system can provide local communities with a back-up system during black-outs, which may occur in the aftermath of catastrophic events such as natu-ral or man-made disasters. When real-world tests are costly or impossible, agent-based models can be used to investigate possible collective behaviors and ineffi-ciencies of such a system. Despite limitations when extrapolating results from simulation runs to the real world, and several other challenges, we conclude that the utilization of agent-based models can very well aid planners and policy makers in designing more resilient cities.
... One possibility is to create a series of land-use modeling primitives (LUMPs) that exist at one level of abstraction above the available frameworks mentioned earlier. These LUMPs would facilitate the completion of small tasks that could be linked together in a chain to represent an agent behavior in an ABM (similar to the method proposed by Huigen 2004), a land-use or land-cover transition as defined by a statistical model (e.g., logistic regression; see Robinson et al. 2012), or some other representation of LUCC. However, the challenge would be to make these model primitives easily adoptable to a broad set of model frameworks and to modelers with different levels of programming skill. ...
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Research efforts have combined land-use and land-cover change (LUCC) and carbon (C) dynamics to estimate the flux and storage of C under different land-use and land-management regimes (e.g., see Chapters 10 and 11). Ultimately, this research arena seeks to understand the C sequestration implications of different land-use change processes or futures. However, despite the need for simulation tools to produce robust predictions of C dynamics under different land-use and land-cover scenarios, there are relatively few models that integrate LUCC and C cycle dynamics. To be clear, many publications document the C balance of specific land-cover scenarios; however, there is an important distinction between modeling land-use change endogenously (such that it changes dynamically as a result of the modeled processes) and incorporating an exogenous land-cover scenario (with a prespecified set of land-cover data) in a C model. The integration of land-use and C-cycle modeling is necessary for several reasons, most notably for the development and implementation of climate change policy (see Chapter 8). National and international science communities have emphasized the need for integrating land-use and C dynamics (e.g., the International Geosphere-Biosphere Programme [IGBP], Global Land Project [GLP], International Human Dimensions Programme on Global Environmental Change [IHDP]; see Chapter 1); however, the C and LUCC modeling communities often operate as somewhat disparate fields of research. Development of international climate negotiations and treaties, such as the Kyoto Protocol and the United Nations Framework Convention on Climate Change Good Practice Guidance for Land Use, Land-Use Change, and Forestry (UNFCCC GPG-LULUCF), relies on current estimates of C pools and fluxes, as well as our expectations for how land-use change will influence C dynamics in the future.
... Especially the parameterization of agent behavior in models for real case-studies turned out to be very complex. However, more recently a larger number of applications of agent-based models to real case studies worldwide have been published, showing the potential of the approach to explore the land change dynamics in local to regional level case studies (Le et al. 2012 ;Robinson et al. 2012 ;Valbuena et al. 2010b ). At larger spatial scales, ranging from the region to the global level the principles of agent-based modeling have not yet been applied in simulation models, leaving most models at that level with highly simplifi ed representations of human-environment interactions (Rounsevell and Arneth 2011 ). ...
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Land change is the result of multiple human-environment interactions operating across different scales. The processes of land change are connected across scales with multiple feedbacks leading to so-called ‘teleconnections’ in the earth system. Local context may cause the same process to result in different trajectories of land change in different world regions: globalization of food production may cause deforestation in tropical regions while valuable agricultural landscapes in other regions are abandoned. Land change models provide a platform for integrating social science and natural science perspectives on human-environment interactions across multiple spatial scales. To reconstruct historic changes and predict future changes in the land system a wide range of different conceptual and simulation models are used. At local scales much advancement has been made in the representation of human behavior and decision making by feeding narrative and empirical research into agent-based modelling. These advances have not been included in global scale land change models where land change is mostly simulated by simple indicators of biophysical suitability or economic rational decision making. Ignoring spatial and temporal variation in decision making across different socio-cultural contexts and not assessing the responses to environmental change leads to inaccuracies in land change assessment outcomes and difficulties in using these models to design place-based strategies for natural resource management and adaptation to global change. This chapter will review different ways in which human-environment interactions are conceptualized in land change modeling at different scales. Based on this review the prospects for using land change models as a platform for integrating social science knowledge are discussed.
... The number of researchers involved in modelling agents' behavior has increased significantly over the last years (Crooks and Heppenstall, 2012). The so-called agentbased models are developed to better understand the theories of political identity and stability (Lustick 2002); economic processes as dynamic systems of interacting agents (Tesfatsion 2006); company size and growth rate distributions (citealtA99); burglary activities (Malleson et al. 2010); size-frequency distributions for traffic jams (Nagel and Rasmussen 1994); spatial patterns of unemployment (Topa 2001); size distributions of cities (Mansury and Gulyás 2007); land system dynamics and wellbeing (Robinson et al. 2012); and so on. However, until recently, agent-based models are not well established in spatial economic research mainly due to the lack of microfoundations underlying individual motivation and behavior. ...
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This paper combines game theory and agent-based modelling, two powerful tools that economists use to understand the behavior of economic agents. We construct an agent-based version of Hotelling’s two-stage game of spatial competition and explore the possibilities of creating synergies between the two approaches. Game theoretic insights into strategic behavior and equilibrium states can provide useful theoretic underpinnings for agent-based approaches in regional science. By combining the two, we can model micro-based social order as it emerges out of local interactions. The use of agent-based modelling in the context of a multistage game is new and hence provides a valuable contribution to both streams of the literature. We show that combining the two approaches is feasible, also in the context of a more complex two-stage game. The model correctly reproduces the analytical results and also allows for more complex situations. As an example, we show the effect of different levels of consumer tastes for variety in Main Street. The reconstruction of Hotelling’s model of spatial competition opens up a wide variety of possibilities for further extensions that can lead to a better understanding of the variations we observe in reality. For some extensions, the use of a single-stage model would probably be more feasible though.
... 4 The influence of governmental policies on herdsmen's wellbeing. Policy decisions related to land use play a significant role in shaping the current state of ecosystems and human well-being in all contexts, thereby implying the need for more informed decision making by governments [58]. The efficacy of the implementation of a policy by the government also depends on the attitude of citizens towards these problems and their understanding of the measures to be implemented under the government's plan [59].According to 40.3% of the surveyed sample, the governmental policies of "return farmland to forests and animal breeding grounds to grassland" have effectively controlled grassland desertification. ...
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Inner Mongolia is among the most important regions in terms of contribution to the socio-economic development of China. Furthermore, its grassland is a major ecological barrier for Northern China. The present study evaluates the changes in ecosystem services availability and human wellbeing based on a survey on864 herdsmen of the grassland and 20 governmental officials. The survey provided the following results: (1) The supporting and provisioning services of the grassland have recently declined, thus affecting the herdsmen's wellbeing. The intensity of grazing, coal exploitation and tourism development heavily limits the availability of ecosystem services, among which provisioning ones are perceived as the most important. Below a certain threshold, grazing and mining are likely to promote the improvement of herdsmen's wellbeing, while trespassing that point, the enhancement of the herdsmen's living standards is curbed. (2) The herdsmen's cultural exchange, health conditions and social relations are better now than before; however, the threats on herdsmen's health and safety have increased. (3) A better income is among the most urgent herdsmen's needs. Livestock revenues did not increase at the same rate as the damage to the grassland and human risk exposure did. (4) The governmental ecological compensation policy did not entirely solve the problem of grassland desertification and environmental degradation, although it is also true that the degree of implementation and effectiveness of government policies is related to the still insufficient herdsmen's understanding and acceptance of these policies.
... Agent-based models (ABMs) have become an important tool for natural resource management and other disciplines (e.g., anthropology, Kohler and Gumerman, 2000;ecology, Grimm et al., 2005; land use and land cover change, Robinson et al., 2012) in recent decades, and for the study of agricultural land-management in particular (e.g., Becu et al., 2003;Bell, 2011;Bert et al., 2010). Where household-level decisions, made in interaction with other households and the natural environment, shape outcomes at the landscape scale, ABMs can provide insights that coarser equation-based models 1 (EBMs) or statistical models may not (Bankes, 2002;Parunak et al., 1998). ...
... In this matter, ABS has been extensively used to study urban growth phenomena (Huang et al., 2013;Matthews et al., 2007) where it supports the representation of different rich individual profiles, normally parametrised from quantitative surveys (Robinson et al., 2012). ...
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The task of green space allocation in urban areas consists of identifying a suitable site for allocating green areas. In this proposition paper we discuss about a number of factors like crowdedness, design, distribution and size that could discourage inhabitants to visit a certain green urban area. We plan to cluster our urban residents into several population segments using an Agent-Based Model and study the system in different predefined scenarios. The overall objective of this work is to provide spatial guidance to planners, policy- makers and other stakeholders, and shed light on potential policy conflicts among standard policy criteria and user preferences. We will evaluate this potential within a targeted stakeholder workshop.
... One of the most common interests in such work is the study of the dynamics involved in urban growth, which is linked with the relative distribution of urbanised, industrial and green spaces along with their impact on qualityof-life issues, and how these factors depend on the broad strategies in place for land-use [6]. ...
Conference Paper
Urban green spaces play a crucial role in the creation of healthy environments in densely populated areas. Agent-based systems are commonly used to model processes such as green-space allocation. In some cases, this systems delegate their spatial assignation to optimisation techniques to find optimal solutions. However, the computational time complexity and the uncertainty linked with long-term plans limit their use. In this paper we explore an approach that makes use of a statistical model which emulates the agent-based system’s behaviour based on a limited number of prior simulations to inform a Genetic Algorithm. The approach is tested on a urban growth simulation, in which the overall goal is to find policies that maximise the inhabitants’ satisfaction. We find that the model-driven approximation is effective at leading the evolutionary algorithm towards optimal policies.
... However, there is much active research in this area, whereby researchers interested in urban planning and sustainability have investigated a range of agent-based systems and similar mechanisms to explore the consequences of different strategies [Parker et al., 2003, Sasaki and Box, 2003, Sanders et al., 1997. One of the most common interests in such work is the dynamics of urban growth, which is linked with the relative distribution of urbanised, industrial and green spaces and their impact on quality-of-life issues, and how these depend on the broad strategies in place for land-use [Robinson et al., 2012]. In many agent based systems, a typical agent represents a local government decision-maker, or a recent immigrant deciding where to settle within the growing city. ...
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Agent-based systems are commonly used in the geographical land use sciences to model processes such as urban growth. In some cases, agents represent civic decision-makers, iteratively making decisions about the sale, purchase and development of patches of land. Based on simple assumptions, such systems are able broadly to model growth scenarios with plausible properties and patterns that can support decision-makers. However, the computational time complexity of simulations limits the use of such systems. Attractive possibilities, such as the optimisation of urban growth policies, tend to be unexplored since the time required to run many thousands of simulations is unacceptable. In this paper we address this situation by exploring an approach that makes use of a statistical model of the agent-based system's behaviour to inform a rapid approximation of the fitness function. This requires a limited number of prior simulations, and then allows the use of an evolutionary algorithm to optimise urban growth policies, where the quality of a policy is evaluated within a highly uncertain environment. The approach is tested on a typical urban growth simulation, in which the overall goal is to find policies that maximise the 'satisfaction' of the residents. We find that the model-driven approximation of the simulation is effective at leading the evolutionary algorithm towards policies that yield vastly better satisfaction levels than unoptimised policies.
Chapter
Land-use models are by now an accepted method in scientific research, both to increase our understanding of land-use change processes and to project future land-use trajectories. Many of these models simulate changes as a function of spatial data layers, such as elevation, accessibility and soil type. However, land-use changes are ultimately the result of human decisions. Therefore representing human decision-making processes in models is essential to advance our understanding of land-use change processes as well as our capacity to support policy making. Agent-based models allow human decision-making to be represented explicitly. However, their application is constrained by the availability of data about actors and their decision-making processes. Empirical data can be obtained from case studies, but the geographic extent of these case studies is constrained by time and resources. Therefore we argue that we need new sources of data to support model representation of these processes. In this chapter, we further specify this data demand and discuss potential methods of data acquisition. Data acquisition methods include metastudies, aligning with various ongoing large-scale data collection efforts, dedicated projects and crowdsourcing.
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Agricultural decision-making processes occur in complex and dynamic environments and are highly contextual. Despite evidence to the contrary, utility maximization is often the implicit theoretical assumption underlying agricultural decision-making processes. This study undertakes an exploratory approach to test alternative theories of human decision-making on the process of agricultural adaptation of farmers in India by synthesizing multiple sources of social and environmental data. We developed an empirical agent-based model (ABM) to simulate past adoption decisions of six agricultural adaptation strategies of 959 farmers in northern India. The model assessed the fit of four major decision-making rules – utility maximization, self-satisficing, social norms, and random choice for farmers differentiated by farm size. Scenario analysis was conducted to test whether (and which) alternative decision-making rules offered a better explanation of the adoption of (which) adaptation strategies. Results demonstrated that the utility-maximizing decision rule had a higher fit for productivity-enhancing adaptation strategies, such as adopting high yield varieties and enhanced fertilizer use, with model performance increasing, generally, with farm size. The adoption of climate tolerant varieties by farmers was most closely guided by self-satisficing and social norms decision-rules, with the model performance, under both scenarios, highest for marginal landholders. Marginal farmers are more likely to use these heuristics to adopt climate tolerant varieties as their decisions may not necessarily be geared towards increasing profit, unlike larger farmers. Social norms had a higher fit for the adoption of climate-related strategies, including enhanced irrigation, with model fit increasing, generally, with farm size. Agricultural policy and extension efforts that incorporate the varied motivations and heuristics of agricultural decision-making, rather than assuming adaptation as a utility maximization exercise, can better design, develop, and disseminate solutions to support the adaptive capacity of farmers.
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کیفیت کیفیت زندگی توانمندی محیط برای تولید و پاسخ گویی به نیازهای مادی و معنوی جامعه جامعه است ؛ به نوع ای که یکی از مهمترین اهداف برنامه ریزان و افزایش شهری کیفیت زندگی در شهرها و بالابردن میزان رضایتمندی در بین شهروندان است. هدف از این تحقیق کیفیت زندگی شهری با استفاده از تحلیل تصمیم گیری چندمعیار مکانیکی است. محدودة موردمطالعه در این تحقیق منطقة 6 است. معیارهای مورد نیاز برای شناخت وضعیت کیفیت محیط زیست شهری شامل معیارهای سبزینگی ، سطح زمین ، آلودگی هوا ، آلودگی صوتی ، و ساختمان آسیب پذیر است. در این تحقیق ، از روش تلفیقی AHP-OWA برای استفاده و تولید نقش کیفیت محیط زیست زندگی شهری استفاده شده است. نتیجة بدست آوردن از مدل مورداستفاده در این تحقیق پنج نقش کیفیت محیط زیست زندگی شهری با درجة ریسک انیمیشن متفاوت است که بسیار مناسب ، مناسب ، متوسط ، نامناسب ، و بسیار نامناسب تقسیم بندی شده است. سناریوی بسیار خوش بینانه ریسک انحصاری بالایی در تعیین کیفیت زیست محیطی زندگی شهری دارد و سناریوی بسیار بدبینانه باعث می شود ریسک انیمیشن در تصمیم گیری برای کیفیت زیست محیطی زندگی شهری کاهش یابد. نتایج تحقیق نشان می دهد کیفیت محیط زیست زندگی شهری در سناریوهای طراحی شده در بدبین ترین حالت بیانگر است که هیچ محله ای در گروه بسیار مناسب نیست و سه محله در گروه بسیار نامناسبقرار گرفته شده است ؛ درحالی که در خوش بینانه ترین حالت ، شش محله در گروه بسیار مناسب قرار گرفته و یک محله در گروه بسیار نامناسب قرارگرفته است. به صورت کلی ، محل واقع در جنوب غرب و شرق در شرایط مناسب تری نسبت به مکان مرکز و شمال شرق قرار دارد. نتایج تحقیق نشان می دهد کیفیت محیط زیست زندگی شهری در سناریوهای طراحی شده در بدبین ترین حالت بیانگر است که هیچ محله ای در گروه بسیار مناسب نیست و سه محله در گروه بسیار نامناسبقرار گرفته شده است ؛ درحالی که در خوش بینانه ترین حالت است ، شش محله در گروه بسیار مناسب قرار گرفته و یک محله در گروه بسیار نامناسب قرارگرفته است. به صورت کلی ، محل واقع در جنوب غرب و شرق در شرایط مناسب تری نسبت به مکان مرکز و شمال شرق قرار دارد. نتایج تحقیق نشان می دهد کیفیت محیط زیست زندگی شهری در سناریوهای طراحی شده در بدبین ترین حالت بیانگر است که هیچ محله ای در گروه بسیار مناسب نیست و سه محله در گروه بسیار نامناسبقرار گرفته شده است ؛ درحالی که در خوش بینانه ترین حالت است ، شش محله در گروه بسیار مناسب قرار گرفته و یک محله در گروه بسیار نامناسب قرارگرفته است. به صورت کلی ، محل واقع در جنوب غرب و شرق در شرایط مناسب تری نسبت به مکان مرکز و شمال شرق قرار دارد.
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Various agents are involved in decision-making when built-up land is allocated and regulated, but the roles of these agents must be clarified. To aid this process, the agents in Wu’an (a mining city in China) were classified as government, enterprise and resident, and then their roles were analyzed to establish a decision-making mechanism. The model of physical site selection for enterprises and residents was quantitatively simulated, taking into account the qualitative constraints from government and enterprises. Based on these rules, eight scenarios under economic development-driven scenario (EDdS) series and the environmental conservation-driven scenario (ECdS) series were set up, and vertical and horizontal comparisons were implemented for analysis. Our study showed that the established models could be well fitted for simulation, and that economic development could stimulate the allocation of more built-up land. The most important achievement is that the proposed comparison can effectively distinguish among the roles of various agents, as well as quantify government and enterprise incentives.
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Quality of life is the ability of environment to supplying and supporting the material and spiritual needs of people, which include concepts such as individual well-being (health, healthcare), social welfare (security, environmental quality, etc.) and spatial equity (access and the same distribution services and urban facilities). Quality of life used to be a key concept and an efficient tools for place ranking, identifying and documenting the causes of class differences in the cities and it have been interest to administrators and urban planners. This thesis aims to assess the quality of urban life on the dispersion of population parameters. For this purpose, three basic parameters for assessing the quality of urban life is considered. These parameters include the socio-economic, environmental and spatial equity. For assessing the socio-economic aspect, census data is used. Pearson’s correlation was computed to analyze the relationships among the variables. Further, factor analysis was conducted to extract unique information from the combined dataset. four factors were identified and interpreted as Housing conditions, Working and literacy conditions, Educational status and activity status and income respectively. Each factor was viewed as a unique aspect of socio-economic parameter of the quality of life. As well as to assess the environmental parameter of quality of life by using satellite imagery and geospatial data some information like maps of NDVI index, land surface temperature, air pollution and noise pollution were extracted, and final index of the environmental parameter was obtained by integration of them.. For evaluating spatial equity two indicators, Accessibility and mixed land use was considered. Equal distribution and access to urban services was measured by these two indicators. This evaluation done for the educational, health, commercial, parks, sports, religious and cultural land use. To investigate the spatial distribution of QOL index, Moran's spatial autocorrelation is used. The results showed that the quality of life index in the studied region is clustered and places by similar value are neighbor. Finally, for investigate the relationship between final extracted index for each aspect of quality of life with each other, the Pearson correlation analysis was used. The results showed a positive correlation between socio-economic index with spatial equity (0.543) and environmental index (0.415). Actually making some basic change in these aspect of QOL can result in reducing of difference between QOL of poor and rich zone of city and can supply the basis of improvement of them. Also it can change the situation of equality and justice in all aspect QOL. Keywords: Quality of Life, Principal Component Analysis, Spatial equity, Environment.
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Rescue centers provide services to victims in critical rescue situations. To select the proper location for new centers and optimal allocation of resources to those centers, at first it's necessary to assess the current state of the centers. Experimental measurements of performance is one of the common methods. The aim of this study was to calculate the efficiency of rescue centers through their performance within a year. DEA model was used to calculate performance. The number of personnel, rescue vehicles, ambulances and equipment are considered as input parameters and the number of events, distance between the center and the location of victims, the time to reach the victims and the number of victims are measured as output parameters of the model. In this article, 13 centers in province of Mazandaran and 27 Center of Province of Gilan were studied. According to the results, 9 rescue centers have good performance and of 31 rescue centers are inefficient. Key word: Data Envelopment Analysis, Rescue centers, Geospatial Information System
Chapter
Landscape pattern characterization aims to map, quantify, and interpret landscape spatial patterns, and is therefore a fundamental pursuit in landscape ecology. The advances in remote sensing and geographic information systems (GIS) have greatly contributed to the development of quantitative methods for landscape pattern characterization. This chapter will review the utilities of remote sensing and GIS for the measurement, analysis, and interpretation of landscape spatial patterns. While remote sensing allows a direct observation of landscape patterns and processes at various scales, GIS provides a technical platform for data integration and synthesis in support of landscape pattern analysis and modeling. The chapter will begin with an overview on the research status identifying some gaps when landscape ecologists utilize remote sensing and GIS techniques in their research. Then, it will examine the utilities of remote sensing and landscape metrics for landscape pattern mapping and quantification, which will be followed by a discussion on GIS-based spatial analysis and modeling techniques for examining patterns, relationships, and emerging trends and for simulation and prediction. While the topics covered in this chapter span the entire spectrum in landscape pattern characterization, our emphasis is not on a comprehensive review but on some methodological issues highlighting caveats and cautions when using remote sensing and geospatial techniques. We believe the issues identified here can help landscape ecologists to better utilize remote sensing and GIS techniques in their specific applications. © Springer Science+Business Media Dordrecht 2013. All rights are reserved.
Chapter
Diagnosis of the problem needs to precede the design of public policies. Usually the diagnosis identifies a problem, but sometimes, a diagnosis will also give some idea of its magnitude. The policy will likely then be designed to minimize or avoid. This is the case when the problem is evident and a solution is urgently required. However the origin of the problem is rarely evaluated in depth and it is even more rare for a multi-sectoral approach to be used. For example, in the health sector, an epidemic such as influenza A (H1N1) which occurred in 2009 in Mexico, resulted in policies directed to a rapid solution to minimize the effects, with no attempt at all to diagnose causes, or understand the roots that gave rise to the situation. Sometimes the origins are considered structural and beyond the attention of the health sector. Many studies suggest that the origin of health problems is to be found, at least partially, in the environment, and not merely in the pathogens, and that the environmental conditions responsible are related to land use change. This indicates that there is a need to extend medical research to link with disciplines such as human and physical geography. General Systems Theory (GST) can indicate the links between territorial processes and health outcomes, and suggests that for communities dealing with health problems it is necessary to start at the local level with management decisions taken locally with regards to the local environment and territory. In the theoretical framework of complex and open systems, there are exchange flows in and out, with other systems. Matter and energy are often considered the most relevant flows. However, flows such as information, capital or cultural values such as affection are difficult to assess. What we are proposing is to study territorial processes, such as land use and land use change, which give rise to serious health problems, such as tuberculosis (TB), and diseases which relate to nutritional status, even in countries with high levels of development We apply GST, to explain how this works. For this application, we truly need interdisciplinary teams that allow us to place the problems in context and uncover their roots. The result of this should give rise to policies designed to fight the underlying causes of the diseases rather than treating the diseases themselves with palliatives, and it should, in the long run, do more for the territory health and increase the community resilience.
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Urban systems are complicated systems where land-use changes may significantly affect the environment and the ecosystem. Therefore, modeling urban growth is crucial for urban planners and administrators to support sustainable development. This paper provides a spatially disaggregated model for urban growth simulation that is characterized by the innovative idea that considers the behavior of residents and couples the explorations of the game between farmers and governments in the land development process. Three kinds of agents, namely, residents, farmers, and governments, make their decisions according to their land use-conversion preferences. Through the use of different strategies that are abstracted from actual land transactions in China, the payoffs to farmers and governments in the game of land expropriation are quantified and then the Nash equilibrium solution of the game is worked out. Those cells with mixed strategy Nash equilibrium solutions that include a probability of greater than 0.5 that either governments will expropriate land legally or that farmers will accept the land acquisition of the governments are referred to as "candidate regions for urban expansion." Based on how they evaluate the "candidate region" condition according to the surrounding environment and land price, residents determine the final land-use transition of each cell in the candidate region that is formed in the previous step. Jiangxia, a suburban area in Wuhan, is used as a case study area to simulate the spatial and temporal dynamics of urban growth. The proposed model, which couples game theory and human decision making in the land-development process, can effectively represent and simulate the spatiotemporal dynamics and patterns of urban growth as well as explain the driving mechanism of urban expansion.
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China has been experiencing the exceptionally drastic land-use/cover changes (LUCC) in the last decades. Many techniques focused on the simulation of the single type of land-use change. However, simulating changes between different types of land-use is much more difficult than simulating change for a single type of land-use. The key to simulations based on the Cellular Automata (CA) model is how to define the transition rules. This paper built a localized land-use competition CA model to examine land-use change rules for several land-use candidates under different localized land-use patterns. By this method, the potential transformation amount of each land-use type was calculated and an optimum transition rule was used to balance the amount of land-use changes of complicated types during the simulation period. The total area of each land-use type was predicted by Markov analysis as the global variable during the whole simulation period. This CA-Markov method was adopted to simulate LUCC in Dalian Economic and Technological Development Zone in 1998 and 2009, followed by a comparative experiment. The results show that: (1) The established test method is feasible for exploring the interaction between various land-use classes; (2) This model had high simulation precision, and the Kappa coefficients in urban area, agricultural area and undeveloped area were 0.762, 0.634 and 0.678, respectively; (3) The model proposed in this paper shows a symbolic way to studying the conversion among different land-use types, which could be used to improve the interactive relationship of LUCC.
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This research analyses urban expansion patterns and their eco-risks in the Poyang Lake region in China. A hybrid model consisting of auto-logistic regression, Markov chain and cellular automata (CA) is designed to improve the performance of the standard logistic regression model. An eco-risk assessment (ERA) index by integrating landscape fragmentation index and area weighted eco-service value index is established to promote the effectiveness for dynamically evaluating the environment and eco-security in watersheds. Scenario predictions are introduced to better understand the relationship between urban dynamics and their eco-risks. Three urban development scenarios such as historical development trend (HDT), environment protection priority (EPP) and goal-oriented restriction (GOR) are designed and transplanted into the CA model through the parameter self-modification method. The quantitative analysis results showed that in the period of the past five years, the urban growth primarily concentrated in the metropolitans. The simulations show that under the HDT scenario the urban growth will mainly emerge in the metropolitans, while under the EPP and GOR scenarios the urban growth will expand along with the metropolitans or the road networks and highways, respectively. Moreover, the ERA demonstrated that the GOR scenario was more effective in meeting the goal of environment protection and urban sustainable development for the study area.
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China is facing the pressures of both rapid economic development and environmental protection, and land-use allocation optimization is an important way to manage the conflicts between these pressures and to achieve sustainable development. Optimization of land-use allocation is a nonlinear multiobjective spatial optimization problem, and a purely local simulation model or global optimization model is insufficient to solve it. It is essential to bridge the gap between the two models through the combination of top-down and bottom-up approaches. This study integrates a multiagent system (MAS) that simulates the behaviors of land-use stakeholders with regard to their choices of specific locations, with a genetic algorithm (GA) that simultaneously evaluates and optimizes land-use configurations to meet various regional development objectives. The model is expected to achieve the optimization of land use in terms of the composition and spatial configuration. Caidian District, Wuhan, China, was chosen as the study area to test the model in this paper. The results show that the performance of the coupled model is superior to a pure GA model or MAS model. The optimal configuration improves on the economic output, spatial compactness, and carbon storage of the current configuration and promotes sustainable regional land-use development from the local scale to the regional scale.
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There is an increasing drive to combine agent-based models with empirical methods. An overview is provided of the various empirical methods that are used for different kinds of questions. Four categories of empirical approaches are identified in which agent-based models have been empirically tested: case studies, stylized facts, role-playing games, and laboratory experiments. We discuss how these different types of empirical studies can be combined. The various ways empirical techniques are used illustrate the main challenges of contemporary social sciences: (1) how to develop models that are generalizable and still applicable in specific cases, and (2) how to scale up the processes of interactions of a few agents to interactions among many agents.
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The ability of agent-based models (ABMs) to represent heterogeneity in the characteristics and behaviors of actors enables analyses about the implications of this heterogeneity for system behavior. The importance of heterogeneity in the specification of ABMs, however, creates new demands for empirical support. An earlier analysis of a survey of residential preferences within southeastern Michigan revealed seven groups of residents with similar preferences on similar characteristics of location. In this paper, we present an ABM that represents the process of residential development,within an urban system and run it for a hypothetical pattern of environmental variation. Residential locations are selected by residential agents, who evaluate locations on the basis of preference for nearness to urban services, including jobs, aesthetic quality of the landscape, and their similarity to their neighbors. We populate our ABM with a population of residential preferences drawn from the survey results in five different ways: (1) preferences drawn at random; (2) equal preferences based on the mean,from the entire survey sample; (3) preferences drawn from a single distribution, whose mean and standard deviation are derived from the survey sample; (4) equal preferences within each of seven groups, based on the group means; and (5) preferences drawn from distributions for each of seven groups, defined by group means and standard deviations. Model sensitivity analysis, based on multiple runs of our model under each case, revealed that adding heterogeneity to agents has a significant effect on model outcomes, measured by aggregate patterns of development sprawl and clustering. Key Words: complex,systems; social surveys; spatial modeling; urban sprawl.
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This paper examines the use of evolutionary programming in agent-based modelling to implement the theory of bounded rationality. Evolutionary programming, which draws on Darwinian analogues of computing to create software programs, is a readily accepted means for solving complex computa-tional problems. Evolutionary programming is also increasingly used to develop problem-solving strategies in accordance with bounded rationality, which addresses features of human decision-making such as cognitive limits, learning, and innovation. There remain many unanswered methodological and conceptual questions about the linkages between bounded rationality and evolutionary programming. This paper reports on how changing parameters in one variant of evolutionary programming, genetic programming, affects the representation of bounded rationality in software agents. Of particular interest are: the ability of agents to solve problems; limits to the complexity of agent strategies; the computational resources with which agents create, maintain, or expand strategies; and the extent to which agents balance exploration of new strategies and exploitation of old strategies.
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The use of agent-based models (ABMs) for investigating land-use science ques-tions has been increasing dramatically over the last decade. Modelers have moved from 'proofs of existence' toy models to case-specific, multi-scaled, multi-actor, and data-intensive models of land-use and land-cover change. An international workshop, titled 'Multi-Agent Modeling and Collaborative Planning— Method2Method Workshop', was held in Bonn in 2005 in order to bring together researchers using different data collection approaches to informing agent-based models. Participants identified a typology of five approaches to empirically inform ABMs for land use science: sample surveys, participant observation, field and laboratory experiments, companion modeling, and GIS and remotely sensed data. This paper reviews these five approaches to informing ABMs, pro-vides a corresponding case study describing the model usage of these approaches, the types of data each approach produces, the types of questions those data can answer, and an evaluation of the strengths and weaknesses of those data for use in an ABM.
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This article presents an overview of multi-agent system models of land-use/cover change (MAS/LUCC models). This special class of LUCC models combines a cellular landscape model with agent-based representations of decision making, integrating the two components through specification of interdependencies and feedbacks between agents and their environment. The authors review alternative LUCC modeling techniques and discuss the ways in which MAS/LUCC models may overcome some important limitations of existing techniques. We briefly review ongoing MAS/LUCC modeling efforts in four research areas. We discuss the potential strengths of MAS/LUCC models and suggest that these strengths guide researchers in assessing the appropriate choice of model for their particular research question. We find that MAS/LUCC models are particularly well suited for representing complex spatial interactions under heterogeneous conditions and for modeling decentralized, autonomous decision making. We discuss a range of possible roles for MAS/LUCC models, from abstract models designed to derive stylized hypotheses to empirically detailed simulation models appropriate for scenario and policy analysis. We also discuss the challenge of validation and verification for MAS/LUCC models. Finally, we outline important challenges and open research questions in this new field. We conclude that, while significant challenges exist, these models offer a promising new tool for researchers whose goal is to create fine-scale models of LUCC phenomena that focus on human-environment interactions.
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Most of our global population and its CO2 emissions can be attributed to urban areas. The process of urbanization changes terrestrial carbon stocks and fluxes, which, in turn, impact ecosystem functions and atmospheric CO2 concentrations. Using the Seattle, WA, region as a case study, this paper explores the relationships between aboveground carbon stocks and land cover within an urbanizing area. The major objectives were to estimate aboveground live and dead terrestrial carbon stocks across multiple land cover classes and quantify the relationships between urban cover and vegetation across a gradient of urbanization. We established 154 sample plots in the Seattle region to assess carbon stocks as a function of distance from the urban core and land cover [urban (heavy, medium, and low), mixed forest, and conifer forest land covers]. The mean (and 95% CI) aboveground live biomass for the region was 89±22 Mg C ha−1 with an additional 11.8±4 Mg C ha−1 of coarse woody debris biomass. The average live biomass stored within forested and urban land covers was 140±40 and 18±14 Mg C ha−1, respectively, with a 57% mean vegetated canopy cover regionally. Both the total carbon stocks and mean vegetated canopy cover were surprisingly high, even within the heavily urbanized areas, well exceeding observations within other urbanizing areas and the average US forested carbon stocks. As urban land covers and populations continue to rapidly increase across the globe, these results highlight the importance of considering vegetation in urbanizing areas within the terrestrial carbon cycle.
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We address the question of when the relative complicatedness of spatial agent-based models (ABMs) compared to alternative modelling approaches can be justified. The spectrum of ABM types from simple, abstract models to complicated models aspiring to realism makes a single answer impossible. Therefore we focus on identifying circumstances where the advantages of ABMs outweigh the additional effort involved. We first recall the reasons for building any model: to simplify the phenomena at hand to improve understanding. Thus, the representational detail of ABMs may not always be desirable. We suggest that critical aspects of the phenomena of interest that help us to assess the likely usefulness of ABMs are the nature of the decisions which actors make, and how their decisions relate to the spatio-temporal grain and extent of the system. More specifically, the heterogeneity of the decision-making context of actors, the importance of interaction effects, and the overall size and organization of the system must be considered. We conclude by suggesting that there are good grounds based on our discussion for ABMs to become a widely used approach in understanding many spatial systems.
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This paper presents a range of future, spatially explicit, land use change scenarios for the EU15, Norway and Switzerland based on an interpretation of the global storylines of the Intergovernmental Panel on Climate Change (IPCC) that are presented in the special report on emissions scenarios (SRES). The methodology is based on a qualitative interpretation of the SRES storylines for the European region, an estimation of the aggregate totals of land use change using various land use change models and the allocation of these aggregate quantities in space using spatially explicit rules. The spatial patterns are further downscaled from a resolution of 10 min to 250 m using statistical downscaling procedures. The scenarios include the major land use/land cover classes urban, cropland, grassland and forest land as well as introducing new land use classes such as bioenergy crops.
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We use a GIS-based agent-based model (ABM), named dynamic ecological exurban development (DEED), with spatial data in hypothetical scenarios to evaluate the individual and interacting effects of lot-size zoning and municipal land-acquisition strategies on possible forest-cover outcomes in Scio Township, a municipality in Southeastern Michigan. Agent types, characteristics, behavioural methods, and landscape perceptions (i.e. landscape aesthetics) are empirically informed using survey data, spatial analyses, and a USDA methodology for mapping landscape aesthetic quality. Results from our scenario experiments computationally verified literature that show large lot-size zoning policies lead to greater sprawl, and large lot-size zoning policies can lead to increased forest cover, although we found this effect to be small relative to municipal land acquisition. The return on land acquisition for forest conservation was strongly affected by the location strategy used to select parcels for conservation. Furthermore, the location strategy for forest conservation land acquisition was more effective at increasing aggregate forest levels than the independent zoning policies, the quantity of area acquired for forest conservation, and any combination of the two. The results using an integrated GIS and ABM framework for evaluating land-use development policies on forest cover provide additional insight into how these types of policies may act out over time and what aspects of the policies were more influential towards the goal of maximising forest cover.
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The ecosystem service concept has emphasized the role of people within socio-ecological systems (SESs). In this paper, we review and discuss alternative ways of representing people, their behaviour and decision-making processes in SES models using an agent-based modelling (ABM) approach. We also explore how ABM can be empirically grounded using information from social survey. The capacity for ABM to be generalized beyond case studies represents a crucial next step in modelling SESs, although this comes with considerable intellectual challenges. We propose the notion of human functional types, as an analogy of plant functional types, to support the expansion (scaling) of ABM to larger areas. The expansion of scope also implies the need to represent institutional agents in SES models in order to account for alternative governance structures and policy feedbacks. Further development in the coupling of human-environment systems would contribute considerably to better application and use of the ecosystem service concept.
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The papers in this special issue, resulting from two workshops intended to chart the way forward for studies of complex land-use dynamics, suggest that the paradigm of ‘complexity’, in its multiple meanings, raises both new opportunities and new challenges that require multidisciplinary attention. The opportunities include the potential to explore non-linear interactions between social and environmental processes in a way that represents the richness of human behavior and ecological functioning, and the mutual dependence of these systems. Computer simulations of agent-based systems provide this opportunity. The challenges are both conceptual and methodological. The case studies being conducted and the models being built are sufficiently complex that comparison and generalization are difficult. Nevertheless, comparisons are possible, and it is important for the land use science community to work towards the goals of comparison and generalization.
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It is not yet completely understood how on-site costs for infrastructures in residential developments vary with lot size and how developers respond to this relationship. Utilizing data from public records of costs for constructing twenty-eight subdivisions in South Kingstown, RI, this paper examines how developers’ on-site costs per lot for sewer and water services and roads vary with lot size. Contrary to previous results, this study finds that these on-site costs per lot can decrease as lot sizes increase. The literature on decision making by developers suggests that this cost relationship can be advantageous to small satisficing developers, leading them to prefer larger lots. To encourage small developers to build denser developments on smaller lots, local governments should consider incurring the upfront costs of certain on-site infrastructures and be reimbursed by developers when the lots are sold.
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An agent-based model was developed as a tool designed to explore our understanding of spatial, social, and environmental issues related to land-use/cover change. The model focuses on a study site in a region of the Amazon frontier, characterized by the development of family farms on 100-ha lots arranged along the Transamazon highway and a series of side roads, west of Altamira, Brazil. The model simulates the land-use behaviour of farming households on the basis of a heuristic decisionmaking strategy that utilizes burn quality, subsistence requirements, household characteristics, and soil quality as key factors in the decisionmaking process. Farming households interact through a local labour pool. The effects of the land-use decisions made by households affect the land cover of their plots and ultimately that of the region. This paper describes this model, referred to as LUCITA, and presents preliminary results showing land-cover changes that compare well with observed land-use and land-cover changes in the region.
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The health effects of community noise are considered to be a more and more important public health issue. In many cities of the world, high levels of noise prevail in the vicinity of busy streets and airports and in indoor environments. The guidelines for noise exposure prevention published by the WHO in 1980 have been updated and revised in 1992-1995, and finalised in 1999. Health-based guidelines have to be applied within a framework of noise management. Key issues of noise management include abatement options, models for forecasting and assessment of effectiveness of source control action, standards setting process for existing and future sources, noise assessment, and testing compliance with noise standards. All these issues are addressed in the new WHO Guidelines for Community Noise, which were published recently.
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We demonstrate an approach for integrating social and ecological models to study ecosystem management strategies. We focus on the management of lake eutrophication. A model has been developed in which the dynamics of the lake, the learning dynamics of society, and the interactions between ecology and society are included. Analyses with the model show that active learning is important to retain the resilience of lakes. Although very low levels of phosphorus in the water will not be reached, active learning reduce the chance of catastrophic high phosphorus levels.
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Background: It is not clear if relationships between GIS obtained environmental features and physical activity differ according to the method used to code GIS data. Methods: Physical activity levels of 210 Boy Scouts were measured by accelerometer. Numbers of parks, trails, gymnasia, bus stops, grocery stores, and restaurants within the commonly used 400 m and 1-mile (1609.3 m) buffers of subject residences and distance to the nearest feature were calculated. Residential density, connectivity, and crime rate were calculated. Regression models with minutes of sedentary, light, or moderate-to-vigorous activity as dependent variables and environmental and demographics as independent variables were run with backward deletion of environmental variables. Results: Park, crime, and gym variables were associated with physical activity, but relationships varied according to whether a 400 m, 1 mile, or nearest criteria was used. Conclusion: Environmental variables were associated with the physical activity of adolescent males, but the association was method dependent.
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This important document replaces the 1980 Environmental Health Criteria No.12 – Noise. It is destined to become widely used and quoted in relation to environmental noise problems. All who have even a passing involvement in this area must become familiar with it and with its recommended levels. The Report considers noise sources and their measurement, adverse effects on health and noise management, whilst introducing a new set of recommendations and guideline values to take account of changes in knowledge and expectations over the past 20 years. Attention is drawn to inadequacies of equivalent level for intermittent noises, to the need to consider effects of low frequency noise and to the rights of vulnerable sub-groups. The Guide can be viewed in full on the World Health Organisation website – www.who.org
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Binary response variables special logistical analyses some complications some related approaches more complex responses. Appendices: Theoretical background Choice of explanatory variables in multiple regression Review of computational aspects Further results and exercises.
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Background Well-designed public open space (POS) that encourages physical activity is a community asset that could potentially contribute to the health of local residents. Methods In 1995–1996, two studies were conducted—an environmental audit of POS over 2 acres (n =516) within a 408-km2 area of metropolitan Perth, Western Australia; and personal interviews with 1803 adults (aged 18 to 59 years) (52.9% response rate). The association between access to POS and physical activity was examined using three accessibility models that progressively adjusted for distance to POS, and its attractiveness and size. In 2002, an observational study examined the influence of attractiveness on the use of POS by observing users of three pairs of high- and low-quality (based on attractiveness) POS matched for size and location. Results Overall, 28.8% of respondents reported using POS for physical activity. The likelihood of using POS increased with increasing levels of access, but the effect was greater in the model that adjusted for distance, attractiveness, and size. After adjustment, those with very good access to large, attractive POS were 50% more likely to achieve high levels of walking (odds ratio, 1.50; 95% confidence level, 1.06–2.13). The observational study showed that after matching POS for size and location, 70% of POS users observed visited attractive POS. Conclusions Access to attractive, large POS is associated with higher levels of walking. To increase walking, thoughtful design (and redesign) of POS is required that creates large, attractive POS with facilities that encourage active use by multiple users (e.g., walkers, sports participants, picnickers).
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Policy makers in Denmark are increasingly recognising the potential health benefits associated with green space, in particular with the use of green space. Knowledge on how green space is used, why it is used, and which factors influence its use, is becoming interesting for researchers, city planners and managers of green space. The present study is based on data from a nationwide study of 11238 randomly selected adult Danes. Respondents were asked about the distance to four different types of green space, their frequency of use of each of these types of green space, and the main reasons for visiting green space. Multiple logistic regression analysis was used to investigate the association between potential predictor factors and visits to green space at least a few times per week. Results show that 66.9% of the respondents live within 300m of green space, 43.0% visit green space every day and 91.5% visit green space at least once a week. Only 0.9% never visit green space. To enjoy the weather and get fresh air is the most important reason for visiting green space for 87.2% of the respondents. Distance to green space is not a limiting factor for the majority of the Danish population and for that reason we recommend a thorough analysis of a neighbourhood or city, its population, and the available green spaces, before deciding on a viable strategy to increase the use of green space.
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The agriculture that occurs in Australia's peri-urban regions is not well understood, nor has its economic value ever been examined systematically. Using a spatial frame derived from research into population change, Agricultural Census data are used to calculate the value of this agricultural production. The analysis suggests that peri-urban regions in the five mainland States produce almost 25% of Australia's total gross value of agricultural production. Evidence gathered from other surveys suggests that, in some respects, this may be an underestimate. Although qualified and provisional, these findings have important strategic implications for agricultural development, urban and regional development and, ultimately, sustainable development. However, peri-urban issues are often submerged in public policy deliberations, and peri-urban agriculture is poorly served by the Agricultural Census.
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Traditional approaches to studying human–environment interactions often ignore individual-level information, do not account for complexities, or fail to integrate cross-scale or cross-discipline data and methods, thus, in many situations, resulting in a great loss in predictive or explanatory power. This article reports on the development, implementation, validation, and results of an agent-based spatial model that addresses such issues. Using data from Wolong Nature Reserve for giant pandas (China), the model simulates the impact of the growing rural population on the forests and panda habitat. The households in Wolong follow a traditional rural lifestyle, in which fuelwood consumption has been shown to cause panda habitat degradation. By tracking the life history of individual persons and the dynamics of households, this model equips household agents with “knowledge” about themselves, other agents, and the environment and allows individual agents to interact with each other and the environment through their activities in accordance with a set of artificial-intelligence rules. The households and environment coevolve over time and space, resulting in macroscopic human and habitat dynamics. The results from the model may have value for understanding the roles of socioeconomic and demographic factors, for identifying particular areas of special concern, and for conservation policy making. In addition to the specific results of the study, the general approach described here may provide researchers with a useful general framework to capture complex human–environment interactions, to incorporate individual-level information, and to help integrate multidisciplinary research efforts, theories, data, and methods across varying spatial and temporal scales.
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Many natural and semi-natural ecosystems are undergoing dramatic conversions resulting from rapid growth in rural home construction. Yet, rates and drivers of rural residential expansion into previously agricultural and natural landscapes have not been widely analyzed. Immigration and rural development have been exceptionally rapid in the private lands surrounding Yellowstone and Grand Teton National Parks, known as the Greater Yellowstone ecosystem (GYE). Because the GYE has unique ecological value, is still largely undeveloped, and is currently characterized by unrestrictive land use policies, there are prime opportunities for improving regional growth management via the incorporation of scientific knowledge into local land use planning decisions. We quantified rates of growth in rural home construction in the GYE and considered the extent to which biophysical and socio-economic factors explained variation in the spatial pattern of rural home development. We applied generalized linear models and use versus availability analyses to examine specific hypotheses regarding the potential drivers of rural residential development. From 1970 to 1999, the GYE experienced a 58% increase in population and a 350% increase in the area of rural lands supporting exurban housing densities. By 1999, one third of exurban developments were distributed in remote rural locations. Patterns of rural development within the GYE have been strongly influenced by agricultural suitability, transportation and services, natural amenities, past development patterns, and economic and recreational characteristics of nearby towns. The proportion of homes built on highly productive soils and lands proximate to water has remained consistently high throughout the 1900s. We suspect that newer homes continue to be built near water and productive soils because of the influence of early settlement patterns and transportation routes. Our data suggest that the more productive farmlands will likely continue to experience a disproportionate level of development pressure, as will the biologically diverse riparian habitats and the private lands bordering the national parks. This pattern of development has the potential to erode the quality of the lowland habitats most used by park wildlife. Although the possibility exists for continued land use intensification in the GYE, we emphasize the potential for local policy decisions to effectively manage growth in rural residential development.
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